Reinforcement Learning
stable-baselines3
PandaReachDense-v2
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use tmilushev/a2c-PandaReachDense-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use tmilushev/a2c-PandaReachDense-v2 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="tmilushev/a2c-PandaReachDense-v2", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download vec_normalize.pkl from tmilushev/a2c-PandaReachDense-v2: direct link, hf CLI and curl.
- Browser
- Download file 3.21 kB
-
https://huggingface.co/tmilushev/a2c-PandaReachDense-v2/resolve/main/vec_normalize.pkl
- Command line
-
hf download hf://tmilushev/a2c-PandaReachDense-v2/vec_normalize.pkl
-
curl -L -o vec_normalize.pkl https://huggingface.co/tmilushev/a2c-PandaReachDense-v2/resolve/main/vec_normalize.pkl
3.21 kB
- Xet hash:
- 386bafdad6b275c33b180c0ccdac7f07a1123fe8b47895a7d1f0fac655adb9cb
- Size of remote file:
- 3.21 kB
- SHA256:
- d46f9d23eec93a68eb08864e83cb6e579860ea99a970f24387ca75e3a344a551
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